Transport Physics and UQ

Marvin L. AdamsTexas A&M University

CRASH Annual ReviewAnn Arbor, MI

October 28-29, 2010

The integrated team has produced significant results this year.

Collaboration has been fruitful and essential.o UQ is a tightly integrated UM/TAMU/SFU effort.o Theoretical understanding has advanced via collaboration

(UM/TAMU).o Radiation has been an integrated UM/TAMU effort; this

continues on more fronts as PDT & CRASH-MG mature.

This talk describes recent TAMU contributions.o Includes UQ, Radiation, and theory.o Much involves collaboration with UM and/or SFU; the

remainder is part of integrated CRASH plan. We are an integral part of the team.

Radiation effort is challenged by prohibition on coupling.

Key task is assessment of diffusion model error.o diffusion model error ≈ [hi-res transport] – [hi-res diffusion]o Must translate no-hydro results to rad-hydro problemo Must address diffusion discretization error

High-res transport tool is PDT (TAMU code).

We employ a no-hydro “CRASH-like” test problem.

We have developed a technique for using a transport code (e.g., PDT) to help assess diffusion model error.

CRASH-like test problem helps us assess model & discretization errors

Constant energy deposition to electrons at “shock”

Can assess effects of o discretization in energy, direction, space, and timeo transport vs. diffusion

Current focus is on ablation layer in plastico See Morel’s talk

4 mm

.3125 mm

Be0.008 g/cc

Au19.3 g/cc

Xe0.018 g/cc

Xe0.1 g/cc

Xe0.0059 g/cc

plastic1.43 g/cc

electron energy source

PDT now solves CRASH-relevant problems.

Continually adding verification tests (McClarren poster)

Performance improvements have enabled solution of relevant problemso 40x serial speedupo 67% efficiency on 12k coreso Team effort (NE+CPSE at A&M)o see poster (“Massively Parallel ...)

There have been many other improvementso electron-energy sources, flexible initial and boundary conditions,

CRASH opacities, better parallel I/O, improved visualization, diffusion preconditioner (debug phase), improved spatial discretizations, improved quadrature sets, etc.

PDT can produce high-resolution transport results for this problem.

Example: o 50 energy groups, S18 quadrature (360 directions), 128 cells in first

0.5 micron of plastic (!), fully implicit solutiono Weekend run, 1024 cores

We are confident that we can assess discretization error and diffusion-model error for this problemo See Morel’s talk

We’ve developed and applied advanced BMARS to CRASH UQ

Recent BMARS progress o Improved BMARS code, comparison with

GP (see posters, papers, Stripling thesis)o Applied to H2D shock breakout (calibrated

flux limiter, wall opacity, and Be EOS)o Built H1D emulator using BMARS and GP (paper

accepted)o Contributors included Mallick,

McClarren, Stripling, Ryu, Bingham, Holloway, and others from UM

See poster on calibration of H2D parameters for shock breakout (Stripling, et al.)

We have developed and disseminated new theoretical results

Theory of thin/thick radiating shocks o Physics of Plasmas,

McClarren/Drake/Morel/Holloway

Verification solutions o JQSRT, McClarren/Wohlbiero Also see McClarren poster

Diffusion model error in radiating shock o JQSRT, Drake/McClarreno Also see Morel talk

We are improving discretization, iteration, parallel, and UQ methods

Assessment of diffusion model and numerical errors: underway; high priority in coming year

New STAPL: PDT transition has begun

Positive spatial discretization: Maginot, et al. poster

Long characteristics spatial discretization: Pandya, et al. poster

Provably optimal sweep schedules: Adams, et al. poster

Diffusion preconditioners for DFEM transport: in progress

Uncertainties from uncertain opacities: dimension-reduction effort in progress

Next year should see further significant advances

PDT will become a more capable CRASH toolo more efficient temperature iterations, including use of diffusion preconditionero RZ geometry; space-time characteristics; DG diffusiono more flexible source and boundary conditions (for verification tests)o Must scale well on BG/L

We will continue to advance UQ methodso include uncertainties in “x” inputso improve emulatoro assess model and discretization erroro compensate for model error?

We will continue theoretical developmentso more verification problems, including analytic 3T solutionso track-based sweepso analyses of iteration and time-differencing methods

Questions?